Models Updating for Technical Objects State Forecasting

Abstract

Under consideration are the forecasting models based on time series systems and multivariate classifiers, which focus on forecasting of technical objects state. In many cases, these models get out of date as new data become available. Therefore, these models require both the model parameters and its structure to be adjusted. The article addresses methods of parameters and structure updating for models applied to predict object state.